EEG Fractal Analysis Reflects Brain Impairment after Stroke

Stroke is the commonest cause of disability. Novel treatments require an improved understanding of the underlying mechanisms of recovery. Fractal approaches have demonstrated that a single metric can describe the complexity of seemingly random fluctuations of physiological signals. We hypothesize that fractal algorithms applied to electroencephalographic (EEG) signals may track brain impairment after stroke. Sixteen stroke survivors were studied in the hyperacute (<48 h) and in the acute phase (∼1 week after stroke), and 35 stroke survivors during the early subacute phase (from 8 days to 32 days and after ∼2 months after stroke): We compared resting-state EEG fractal changes using fractal measures (i.e., Higuchi Index, Tortuosity) with 11 healthy controls. Both Higuchi index and Tortuosity values were significantly lower after a stroke throughout the acute and early subacute stage compared to healthy subjects, reflecting a brain activity which is significantly less complex. These indices may be promising metrics to track behavioral changes in the very early stage after stroke. Our findings might contribute to the neurorehabilitation quest in identifying reliable biomarkers for a better tailoring of rehabilitation pathways.     

Functional magnetic resonance imaging of awake monkeys: some approaches for improving imaging quality

Functional magnetic resonance imaging (fMRI) at high magnetic field strength can suffer from serious degradation of image quality because of motion and physiological noise, as well as spatial distortions and signal losses due to susceptibility effects. Overcoming such limitations is essential for sensitive detection and reliable interpretation of fMRI data. These issues are particularly problematic in studies of awake animals. As part of our initial efforts to study functional brain activations in awake, behaving monkeys using fMRI at 4.7 T, we have developed acquisition and analysis procedures to improve image quality with encouraging results.We evaluated the influence of two main variables on image quality. First, we show how important the level of behavioral training is for obtaining good data stability and high temporal signal-to-noise ratios. In initial sessions, our typical scan session lasted 1.5 h, partitioned into short (<10 min) runs. During reward periods and breaks between runs, the monkey exhibited movements resulting in considerable image misregistrations. After a few months of extensive behavioral training, we were able to increase the length of individual runs and the total length of each session. The monkey learned to wait until the end of a block for fluid reward, resulting in longer periods of continuous acquisition. Each additional 60 training sessions extended the duration of each session by 60 min, culminating, after about 140 training sessions, in sessions that last about 4 h. As a result, the average translational movement decreased from over 500 μm to less than 80 μm, a displacement close to that observed in anesthetized monkeys scanned in a 7-T horizontal scanner.Another major source of distortion at high fields arises from susceptibility variations. To reduce such artifacts, we used segmented gradient-echo echo-planar imaging (EPI) sequences. Increasing the number of segments significantly decreased susceptibility artifacts and image distortion. Comparisons of images from functional runs using four segments with those using a single-shot EPI sequence revealed a roughly twofold improvement in functional signal-to-noise-ratio and 50% decrease in distortion. These methods enabled reliable detection of neural activation and permitted blood-oxygenation-level-dependent-based mapping of early visual areas in monkeys using a volume coil.In summary, both extensive behavioral training of monkeys and application of segmented gradient-echo EPI sequence improved signal-to-noise ratio and image quality. Understanding the effects these factors have is important for the application of high field imaging methods to the detection of submillimeter functional structures in the awake monkey brain.     

Factors Related to Continuation of Health Behaviours among Stroke Survivors

Purpose: This study investigated stroke survivors'' perspectives of health behaviours after stroke. We aimed to explore the actual process by which stroke survivors changed their health behaviours. Method: Semi-structured interviews were conducted with 40 people in a 1-year prospective study in the regional city of Chiba, Japan. Interviews covered views of health behaviours in order to explore why patients change their risk factors. Data were analysed using the principles of modified grounded theory. Results: Six categories related to practising health behaviours were identified: cause of stroke, antithetic thinking, awareness of the body, fear of disease progression, view of health, and psychological meaning of practise. Stroke survivors constructed a meaning of practise for each health behaviour. The recognition of previous lifestyle as cause of stroke, hope for recovery, and fear of future progression influenced health behaviours. Conclusions: The key finding of this study is that when cognitive behavioural therapy principles are enforced, an important aspect is that stroke survivors recognize the possibility that previous lifestyle was a cause of stroke and appreciate the necessity of preventing a new stroke.     

Origins of intersubject variability of blood oxygenation level dependent and arterial spin labeling fMRI: implications for quantification of brain activity

Accurate localization of brain activity using blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has been challenged because of the large BOLD signal within distal veins. Arterial spin labeling (ASL) techniques offer greater sensitivity to the microvasculature but possess low temporal resolution and limited brain coverage. In this study, we show that the physiological origins of BOLD and ASL depend on whether percent change or statistical significance is being considered. For BOLD and ASL fMRI data collected during a simple unilateral hand movement task, we found that in the area of the contralateral motor cortex the centre of gravity (CoG) of the intersubject coefficient of variation (CV) of BOLD fMRI was near the brain surface for percent change in signal, whereas the CoG of the intersubject CV for Z-score was in close proximity of sites of brain activity for both BOLD and ASL. These findings suggest that intersubject variability of BOLD percent change is vascular in origin, whereas the origin of inter-subject variability of Z-score is neuronal for both BOLD and ASL. For longer duration tasks (12 s or greater), however, there was a significant correlation between BOLD and ASL percent change, which was not evident for short duration tasks (6 s). These findings suggest that analyses directly comparing percent change in BOLD signal between pre-defined regions of interest using short duration stimuli, as for example in event-related designs, may be heavily weighted by large-vessel responses rather than neuronal responses.     

What Can Local Transfer Entropy Tell Us about Phase-Amplitude Coupling in Electrophysiological Signals?

Modulation of the amplitude of high-frequency cortical field activity locked to changes in the phase of a slower brain rhythm is known as phase-amplitude coupling (PAC). The study of this phenomenon has been gaining traction in neuroscience because of several reports on its appearance in normal and pathological brain processes in humans as well as across different mammalian species. This has led to the suggestion that PAC may be an intrinsic brain process that facilitates brain inter-area communication across different spatiotemporal scales. Several methods have been proposed to measure the PAC process, but few of these enable detailed study of its time course. It appears that no studies have reported details of PAC dynamics including its possible directional delay characteristic. Here, we study and characterize the use of a novel information theoretic measure that may address this limitation: local transfer entropy. We use both simulated and actual intracranial electroencephalographic data. In both cases, we observe initial indications that local transfer entropy can be used to detect the onset and offset of modulation process periods revealed by mutual information estimated phase-amplitude coupling (MIPAC). We review our results in the context of current theories about PAC in brain electrical activity, and discuss technical issues that must be addressed to see local transfer entropy more widely applied to PAC analysis. The current work sets the foundations for further use of local transfer entropy for estimating PAC process dynamics, and extends and complements our previous work on using local mutual information to compute PAC (MIPAC).     

Across-trial averaging of event-related EEG responses and beyond

Internally and externally triggered sensory, motor and cognitive events elicit a number of transient changes in the ongoing electroencephalogram (EEG): event-related brain potentials (ERPs), event-related synchronization and desynchronization (ERS/ERD), and event-related phase resetting (ERPR). To increase the signal-to-noise ratio of event-related brain responses, most studies rely on across-trial averaging in the time domain, a procedure that is, however, blind to a significant fraction of the elicited cortical activity. Here, we outline the key concepts underlying the limitations of time-domain averaging and consider three alternative methodological approaches that have received increasing interest: time-frequency decomposition of the EEG (using the continuous wavelet transform), blind source separation of the EEG (using Independent Component Analysis) and the analysis of event-related brain responses at the level of single trials. In addition, we provide practical guidelines on the implementation of these methods and on the interpretation of the results they produce.     

Combination of BOLD-fMRI and VEP recordings for spin-echo MRI detection of primary magnetic effects caused by neuronal currents

In the present paper, for the first time, the feasibility to detect primary magnetic field changes caused by neuronal activity in vivo by spin-echo (SE) magnetic resonance imaging (MRI) is investigated. The detection of effects more directly linked to brain activity than secondary hemodynamic–metabolic changes would enable the study of brain function with improved specificity. However, the detection of neuronal currents by MRI is hampered by such accompanying hemodynamic changes. Therefore, SE image acquisition, rather than gradient-echo (GE) image acquisition, was preferred in the present work since the detection of primary neuronal and not blood oxygenation level-dependent (BOLD)-related effects may be facilitated by this approach. First of all, a precise spatiotemporal synchronization of image acquisition with the neuronal event had to be performed to avoid refocusing of the dephasing phenomenon during the course of the SE sequence. At this aim, we propose the combined use of visual evoked potential (VEP) recordings and BOLD-fMRI measurements prior to SE MRI scanning. Moreover, we exemplify by theory and experimentation how the control of artefactual signal changes due to BOLD and movement effects may be further improved by the experimental design. Finally, results from a pilot study using the proposed combination of VEP recordings and MRI techniques are reported, suggesting the feasibility of this method.     

The effects of single-trial averaging on the temporal resolution of functional MRI

Computer simulations and event-related functional MRI (ER-fMRI) experiments were performed to investigate the effects of single-trial averaging and the corresponding contrast-to-noise ratio (CNR) on the minimal resolvable hemodynamic timing difference between brain areas. Three ER-fMRI sessions with temporally delayed (250, 500 and 1,000 ms) visual stimulations between two hemifields, each with 70 repeated single trials, were examined on two subjects. From the computer simulation, the temporal resolution improved as the CNR increased, which reached 500 and 100 ms for CNRs of 1.55 and 6.44, respectively. In the ER-fMRI experiments, the measured CNR increased as more single trials were averaged. The detectability of temporal differences was positively correlated (P<.05) with the CNR in all sessions for one subject but only in the 1,000-ms session for the other subject. Temporal resolution of 1,000 ms was achieved when more than 10 trials were averaged. The 500- and 250-ms delays might be differentiable when more than 20 trials were averaged, but the results were subject-dependent. This study demonstrated that the CNR could be significantly improved by single-trial averaging, which led to an improved temporal resolution of ER-fMRI. Temporal resolution in the range of hundreds of milliseconds was subject-dependent, which might be attributed to the intrinsic spatial variations in the timing of the blood oxygenation level-dependent (BOLD) response.     

Cortex-based independent component analysis of fMRI time series

The cerebral cortex is the main target of analysis in many functional magnetic resonance imaging (fMRI) studies. Since only about 20% of the voxels of a typical fMRI data set lie within the cortex, statistical analysis can be restricted to the subset of the voxels obtained after cortex segmentation. While such restriction does not influence conventional univariate statistical tests, it may have a substantial effect on the performance of multivariate methods.

Here, we describe a novel approach for data-driven analysis of single-subject fMRI time series that combines techniques for the segmentation and reconstruction of the cortical surface of the brain and the spatial independent component analysis (sICA) of the functional time courses (TCs). We use the mesh of the white matter/gray matter boundary, automatically reconstructed from high-spatial-resolution anatomical MR images, to limit the sICA decomposition of a coregistered functional time series to those voxels which are within a specified region with respect to the cortical sheet (cortex-based ICA, or cbICA). We illustrate our analysis method in the context of fMRI blocked and event-related experimental designs and in an fMRI experiment with perceptually ambiguous stimulation, in which an a priori specification of the stimulation protocol is not possible.

A comparison between cbICA and conventional hypothesis-driven statistical methods shows that cortical surface maps and component TCs blindly obtained with cbICA reliably reflect task-related spatiotemporal activation patterns. Furthermore, the advantages of using cbICA when the specification of a temporal model of the expected hemodynamic response is not straightforward are illustrated and discussed. A comparison between cbICA and anatomically unconstrained ICA reveals that — beside reducing computational demand — the cortex-based approach improves the fitting of the ICA model in the gray matter voxels, the separation of cortical components and the estimation of their TCs, particularly in the case of fMRI data sets with a complex spatiotemporal statistical structure.     

Effects of practice with and without knowledge of results on jitter and shimmer levels in normally speaking women

The effects of practice on jitter and shimmer were assessed in two groups of normally speaking women. Subjects in both groups sustained trials of /a/ as steadily as possible during a baseline session, two practice sessions, and a transfer session. Subjects in one group received visual and verbal feedback during the practice sessions. Subjects in the other group received no feedback. Shimmer means remained essentially stable over the four sessions for both groups, and no differences were apparent between the groups. Jitter values were significantly different between sessions for both groups, and between the two groups for the practice sessions. These results are consistent with findings from manual performance and retention tasks. The present findings also support a recently developed neurologic model of jitter.     

Continuous EEG-fMRI in patients with partial epilepsy and focal interictal slow-wave discharges on EEG

Purpose

To verify whether in patients with partial epilepsy and routine electroenecephalogram (EEG) showing focal interictal slow-wave discharges without spikes combined EEG–functional magnetic resonance imaging (fMRI) would localize the corresponding epileptogenic focus, thus providing reliable information on the epileptic source.

Methods

Eight patients with partial epileptic seizures whose routine scalp EEG recordings on presentation showed focal interictal slow-wave activity underwent EEG–fMRI. EEG data were continuously recorded for 24 min (four concatenated sessions) from 18 scalp electrodes, while fMRI scans were simultaneously acquired with a 1.5-Tesla magnetic resonance imaging (MRI) scanner. After recording sessions and MRI artefact removal, EEG data were analyzed offline. We compared blood oxygen level-dependent (BOLD) signal changes on fMRI with EEG recordings obtained at rest and during activation (with and without focal interictal slow-wave discharges).

Results

In all patients, when the EEG tracing showed the onset of focal slow-wave discharges on a few lateralized electrodes, BOLD-fMRI activation in the corresponding brain area significantly increased. We detected significant concordance between focal EEG interictal slow-wave discharges and focal BOLD activation on fMRI. In patients with lesional epilepsy, the epileptogenic area corresponded to the sites of increased focal BOLD signal.

Conclusions

Even in patients with partial epilepsy whose standard EEGs show focal interictal slow-wave discharges without spikes, EEG–fMRI can visualize related focal BOLD activation thus providing useful information for pre-surgical planning.     

Non-neural BOLD variability in block and event-related paradigms

Block and event-related stimulus designs are typically used in fMRI studies depending on the importance of detection power or estimation efficiency. The extent of vascular contribution to variability in block and event-related fMRI-BOLD response is not known. With scaling, the extent of vascular variability in the fMRI-BOLD response during block and event-related design tasks was investigated. Blood oxygen level-dependent (BOLD) contrast data from healthy volunteers performing a block design motor task and an event-related memory task requiring performance of a motor response were analyzed from the regions of interest (ROIs) surrounding the primary and supplementary motor cortices. Average BOLD signal change was significantly larger during the block design compared to the event-related design. In each subject, BOLD signal change across voxels in the ROIs had higher variation during the block design task compared to the event-related design task. Scaling using the resting state fluctuation of amplitude (RSFA) and breath-hold (BH), which minimizes BOLD variation due to vascular origins, reduced the within-subject BOLD variability in every subject during both tasks but significantly reduced BOLD variability across subjects only during the block design task. The strong non-neural source of intra- and intersubject variability of BOLD response during the block design compared to event-related task indicates that study designs optimizing for statistical power through enhancement of the BOLD contrast (for, e.g., block design) can be affected by enhancement of non-neural sources of BOLD variability.     

基于近红外光谱检测技术鉴别洋槐蜜中掺入大米糖浆的可行性研究

利用近红外光谱技术(near infrared spectroscopy,NIR)并结合化学计量学方法鉴别洋槐蜜中掺入大米糖浆的可行性研究。以来自不同蜂场的20个洋槐原料蜜样品与大米糖浆混合成7个不同浓度梯度(10∶0,9∶1,7∶3,1∶1,3∶7,1∶9,0∶10 g·g-1)共121个样品为研究对象,利用近红外光谱仪和光谱处理软件分别不同浓度梯度的对掺假样品进行光谱扫描和数据转换,并进行主成分分析(PCA),结合典型判别分析进行区分。结果表明,经过主成分分析后,前2个主成分的得分累计贡献率达97.23%,但掺假样品在第一、第二主成分得分散点图的区域划分不明显。用典型判别分析进一步判别,所有样本均得到准确的判别,准确率为100%,6个典型判别函数中前两个判别函数的累积贡献率达到91.6%,同时在第一类和第二类典型判别函数的分组图中,不同浓度梯度的掺假蜂蜜能够被较好的判别。表明该方法能够快速、有效鉴别大米糖浆在洋槐蜂蜜中的掺假,具有一定可行性和实用性。     

Exploring vision-related acupuncture point specificity with multivoxel pattern analysis

Acupoint specificity is one of the central issues of functional magnetic resonance imaging (fMRI) studies of acupuncture and has been under discussed. However, strong and consistent proof has not been provided for the existence of acupoint specificity, and unsuitable analysis approach applied could be the reason. We observed that previous researches of acupoint specificity were mostly based on model-based methods which were limited to make exploration of acupoint specificity because of the inaccurate specified prior. Here we applied multi-voxel pattern analysis (MVPA) to investigate the specificity of brain activation patterns induced by acupuncture stimulations at a vision-related acupoint (GB37) and a nearby nonacupoint (NAP). Results showed that multiple brain areas could differentiate the central neural response patterns induced by acupuncture stimulation at these two sites with higher accuracy above the chance level. These regions included occipital cortex, limbic-cerebellar areas and somatosensory cortex. Our results support that the characteristic neural response patterns of brain cortex to the acupuncture stimulation at GB37 and a nearby NAP could differ from each other effectively with the application of MVPA approach.     

Increased BOLD sensitivity in the orbitofrontal cortex using slice-dependent echo times at 3 T

Functional magnetic resonance imaging (fMRI) exploits the blood oxygenation level dependent (BOLD) effect to detect neuronal activation related to various experimental paradigms. Some of these, such as reversal learning, involve the orbitofrontal cortex and its interaction with other brain regions like the amygdala, striatum or dorsolateral prefrontal cortex. These paradigms are commonly investigated with event-related methods and gradient echo-planar imaging (EPI) with short echo time of 27 ms. However, susceptibility-induced signal losses and image distortions in the orbitofrontal cortex are still a problem for this optimized sequence as this brain region consists of several slices with different optimal echo times. An EPI sequence with slice-dependent echo times is suitable to maximize BOLD sensitivity in all slices and might thus improve signal detection in the orbitofrontal cortex. To test this hypothesis, we first optimized echo times via BOLD sensitivity simulation. Second, we measured 12 healthy volunteers using a standard EPI sequence with an echo time of 27 ms and a modified EPI sequence with echo times ranging from 22 ms to 47 ms. In the orbitofrontal cortex, the number of activated voxels increased from 87±44 to 549±83 and the maximal t-value increased from 4.4±0.3 to 5.4±0.3 when the modified EPI was used. We conclude that an EPI with slice-dependent echo times may be a valuable tool to mitigate susceptibility artifacts in event-related whole-brain fMRI studies with a focus on the orbitofrontal cortex.     

Relationship between neural and hemodynamic signals during spontaneous activity studied with temporal kernel CCA

Functional magnetic resonance imaging (fMRI) based on the so-called blood oxygen level-dependent (BOLD) contrast is a powerful tool for studying brain function not only locally but also on the large scale. Most studies assume a simple relationship between neural and BOLD activity, in spite of the fact that it is important to elucidate how the “when” and “what” components of neural activity are correlated to the “where” of fMRI data. Here we conducted simultaneous recordings of neural and BOLD signal fluctuations in primary visual (V1) cortex of anesthetized monkeys. We explored the neurovascular relationship during periods of spontaneous activity by using temporal kernel canonical correlation analysis (tkCCA). tkCCA is a multivariate method that can take into account any features in the signals that univariate analysis cannot. The method detects filters in voxel space (for fMRI data) and in frequency–time space (for neural data) that maximize the neurovascular correlation without any assumption of a hemodynamic response function (HRF). Our results showed a positive neurovascular coupling with a lag of 4–5 s and a larger contribution from local field potentials (LFPs) in the γ range than from low-frequency LFPs or spiking activity. The method also detected a higher correlation around the recording site in the concurrent spatial map, even though the pattern covered most of the occipital part of V1. These results are consistent with those of previous studies and represent the first multivariate analysis of intracranial electrophysiology and high-resolution fMRI.     

Brain modifications after acute alcohol consumption analyzed by resting state fMRI

Resting-state functional magnetic resonance imaging (fMRI) is a recent breakthrough in neuroimaging research able to describe “in vivo” the spontaneous baseline neuronal activity characterized by blood oxygen level dependent (BOLD) signal fluctuations at slow frequency (0.01–0.1 Hz) that, in the absence of any task, forms spatially distributed functional connectivity networks, called resting state networks (RSNs). The aim of this study was to investigate, in the young and healthy population, the changing of the RSNs after acute ingestion of an alcohol dose able to determine a blood concentration (0.5 g/L) that barely exceeds the legal limits for driving in the majority of European Countries. Fifteen healthy volunteers underwent two fMRI sessions using a 1.5 T MR scanner before and after alcohol oral consumption. The main sequence acquired was EPI 2D BOLD, one per each session. To prevent the excessive alcohol consumption the subjects underwent the estimation of blood rate by breath test and after the stabilization of blood alcohol level (BAL) at 0.5 g/L the subjects underwent the second fMRI session. Functional data elaboration was carried out using the probabilistic independent component analysis (PICA). Spatial maps so obtained were further organized, with MELODIC multisession temporal concatenation FSL option, in a cluster representing the group of pre-alcohol sessions and the group of post-alcohol sessions, followed by the dual regression approach in order to evaluate the increase or decrease in terms of connectivity in the RSNs between the two sessions at group level.The results we obtained reveal that acute consumption of alcohol reduces in a significant way the BOLD signal fluctuations in the resting brain selectively in the sub-callosal cortex (SCC), in left temporal fusiform cortex (TFC) and left inferior temporal gyrus (ITG), which are cognitive regions known to be part of the reward brain network and the ventral visual system.     

Rapid head-related transfer function adaptation using a virtual auditory environment

The paper reports on the ability of people to rapidly adapt in localizing virtual sound sources in both azimuth and elevation when listening to sounds synthesized using non-individualized head-related transfer functions (HRTFs). Participants were placed within an audio-kinesthetic Virtual Auditory Environment (VAE) platform that allows association of the physical position of a virtual sound source with an alternate set of acoustic spectral cues through the use of a tracked physical ball manipulated by the subject. This set-up offers a natural perception-action coupling, which is not limited to the visual field of view. The experiment consisted of three sessions: an initial localization test to evaluate participants' performance, an adaptation session, and a subsequent localization test. A reference control group was included using individual measured HRTFs. Results show significant improvement in localization performance. Relative to the control group, participants using non-individual HRTFs reduced localization errors in elevation by 10° with three sessions of 12 min. No significant improvement was found for azimuthal errors or for single session adaptation.     

基于希尔伯特-黄变换的近红外脑功能成像信号分析

近红外光谱技术(Near-infrared spectroscopy,NIRS)已被广泛应用于无损大脑功能检测,然而传统时频分析方法并不适用于非稳态、非线性的血氧信号。在视觉刺激实验中,采集被试前额叶的血氧信号,分别比较了傅里叶谱分析法、小波谱分析法和希尔伯特黄变换(Hilbert-Huang transform,HHT)方法在近红外脑功能成像信号分析中应用的结果。实验表明基于希尔伯特黄变换的谱分析方法优于其它两种方法,并且使近红外光谱研究可以采用事件相关设计的实验,为形成近红外光谱信号分析的标准方法开辟了新的途径。